Autonomous driving vehicles require both a precise localization and mapping solution in
different driving environment. In this context, Simultaneous Localization and Mapping …

Small unmanned aerial vehicles (UAVs) have gained significant interest in the last decade.
More specifically these vehicles have the capacity to impact package delivery logistics in a …

We propose a framework for tightly-coupled lidar inertial odometry via smoothing and
mapping, LIO-SAM, that achieves highly accurate, real-time mobile robot trajectory …

We propose a lightweight and ground-optimized lidar odometry and mapping method, LeGO-
LOAM, for realtime six degree-of-freedom pose estimation with ground vehicles. LeGO …

Accurate and reliable localization and mapping is a fundamental building block for most
autonomous robots. For this purpose, we propose a novel, dense approach to laserbased …

We present LINS, a lightweight lidar-inertial state estimator, for real-time ego-motion
estimation. The proposed method enables robust and efficient navigation for ground …

Recently, transformer architecture has gained great success in the computer vision
community, such as image classification, object detection, etc. Nonetheless, its application …

We present a novel deep convolutional network pipeline, LO-Net, for real-time lidar
odometry estimation. Unlike most existing lidar odometry (LO) estimations that go through …

The development of a navigation system is one of the major challenges in building a fully
autonomous platform. Full autonomy requires a dependable navigation capability not only in …

We present a data processing pipeline to online estimate ego‐motion and build a map of the
traversed environment, leveraging data from a 3D laser scanner, a camera, and an inertial …